Phylogeographic differentiation in the mitochondrial control region in the koala, Phascolarctos cinereus (Goldfuss 1817)

The koala, Phascolarctos cinereus, is a geographically widespread species endemic to Australia, with three currently recognized subspecies: P.c. adustus, P.c. cinereus, and P.c. victor. Intraspecific variation in the mitochondrial DNA (mtDNA) control region was examined in over 200 animals from 16 representative populations throughout the species' range. Eighteen different haplotypes were defined in the approximate to 860 bp mtDNA control region as determined by heteroduplex analysis/temperature gradient gel electrophoresis (HDA/TGGE). Any single population typically possessed only one or two haplotypes yielding an average within-population haplotypic diversity of 0.180 +/- 0.003, and nucleotide diversity of 0.16%. Overall, mtDNA control region sequence diversity between populations averaged 0.67%, and ranged from 0% to 1.56%. Nucleotide divergence between populations averaged 0.51%, and ranged from 0% to 1.53%. Neighbour-joining methods revealed limited phylogenetic distinction between geographically distant populations of koalas, and tentative support for a single evolutionarily significant unit (ESU). This is consistent with previous suggestions that the morphological differences formalized by subspecific taxonomy may be interpreted as clinal variation. Significant differentiation in mtDNA-haplotype frequencies between localities suggested that little gene now currently exists among populations. When combined with microsatellite analysis, which has revealed substantial differentiation among koala populations, we conclude that the appropriate short-term management unit (MU) for koalas is the local population.

Adaptation of sorghum: characterisation of genotypic flowering responses to temperature and photoperiod

Sorghum [Sorghum bicolor (L.) Moench] is an important cereal crop grown in a wide range of tropical and temperate environments. This study was conducted to characterise the photothermal flowering responses of sorghum genotypes and to examine relationships between photothermal characteristics and environment of origin in order to better understand the phenological basis of adaptation to environment in sorghum. Twenty-four germplasm accessions and one hybrid from 24 major sorghum-growing areas were grown in a wide range of environments varying in temperature and photoperiod in India, Kenya and Mall between 1992 and 1995. Times from sowing to flowering (f) were recorded, and the responsiveness of 1/f to temperature and photoperiod was quantified using photothermal models. Times from sowing to flowering were accurately predicted in a wide range of environments using a multiplicative rate photothermal model. Significant variation in the minimum time to flower (F-m) and photoperiod sensitivity (critical photoperiod, P-c, and photoperiod-sensitivity slope, P-s) was observed among the genotypes; in contrast there was little variation in base temperature (Tb) Adaptation of sorghum to the diverse environments in which it is grown was largely determined by photoperiod sensitivity and minimum time to flower; photoperiod sensitivity determines bread adaptation to latitude (daylength), while variation in the minimum time to flower determines specific adaptation within smaller ranges of latitude, e.g. within the humid and sub-humid tropics.

The serotonin transporter gene and Parkinson's disease

Dysfunction in the serotonin (5-hydroxytryptamine) system and reduced serotonin concentrations have been reported in patients with Parkinson's disease (PD). Serotonin concentrations in neural tissue are controlled by a presynaptic serotonin transporter protein that is encoded by a single gene. Therefore, we investigated whether a polymorphic region in the serotonin transporter gene is associated with PD. Three variable-number tandem repeat (VNTR) elements of the serotonin transporter gene were detected by polymerase chain reaction, those with 9, 10, 11 and 12 copies of the repeat element. The 10-copy VNTR element was significantly less common in patients with PD than controls in the univariate analysis (p < 0.05). Logistic regression analysis revealed no significant differences between patients (n = 198) and controls (n = 200) in the distribution frequencies of 9-and 12-copy alleles and combined genotypes (odds ratio = 1.20; p = 1.71). A positive family history of PD was a strong predictor of disease risk (odds ratio = 2.98; 95% confidence interval 1.51-5.87; p = 0.001). Although slight differences were observed between patient and control groups, these data suggest that defects in serotonin concentrations in patients with PD are unlikely to be due to polymorphisms in the serotonin transporter gene in this large Australian cohort; however, the inverse association observed with the 10-copy allele warrants further investigation. Copyright (C) 2000 S. Karger AG, Basel.

Stochastic structure and individual-tree growth models

The majority of past and current individual-tree growth modelling methodologies have failed to characterise and incorporate structured stochastic components. Rather, they have relied on deterministic predictions or have added an unstructured random component to predictions. In particular, spatial stochastic structure has been neglected, despite being present in most applications of individual-tree growth models. Spatial stochastic structure (also called spatial dependence or spatial autocorrelation) eventuates when spatial influences such as competition and micro-site effects are not fully captured in models. Temporal stochastic structure (also called temporal dependence or temporal autocorrelation) eventuates when a sequence of measurements is taken on an individual-tree over time, and variables explaining temporal variation in these measurements are not included in the model. Nested stochastic structure eventuates when measurements are combined across sampling units and differences among the sampling units are not fully captured in the model. This review examines spatial, temporal, and nested stochastic structure and instances where each has been characterised in the forest biometry and statistical literature. Methodologies for incorporating stochastic structure in growth model estimation and prediction are described. Benefits from incorporation of stochastic structure include valid statistical inference, improved estimation efficiency, and more realistic and theoretically sound predictions. It is proposed in this review that individual-tree modelling methodologies need to characterise and include structured stochasticity. Possibilities for future research are discussed. (C) 2001 Elsevier Science B.V. All rights reserved.

Using biplots to interpret gene expression patterns in plants

Sum: Plant biologists in fields of ecology, evolution, genetics and breeding frequently use multivariate methods. This paper illustrates Principal Component Analysis (PCA) and Gabriel's biplot as applied to microarray expression data from plant pathology experiments. Availability: An example program in the publicly distributed statistical language R is available from the web site (www.tpp.uq.edu.au) and by e-mail from the contact. Contact: scott.chapman@csiro.au.

Identification of novel "pathologs" (human disease-related gene candidates) from the RIKEN full-length mouse cDNA data set

The majority of common diseases such as cancer, allergy, diabetes, or heart disease are characterized by complex genetic traits, in which genetic and environmental components contribute to disease susceptibility. Our knowledge of the genetic factors underlying most of such diseases is limited. A major goal in the post-genomic era is to identify and characterize disease susceptibility genes and to use this knowledge for disease treatment and prevention. More than 500 genes are conserved across the invertebrate and vertebrate genomes. Because of gene conservation, various organisms including yeast, fruitfly, zebrafish, rat, and mouse have been used as genetic models.

Patterns of variation within self-incompatibility loci

Diverse self-incompatibility (SI) mechanisms permit flowering plants to inhibit fertilization by pollen that express specificities in common with the pistil. Characteristic of at least two model systems is greatly reduced recombination across large genomic tracts surrounding the S-locus, which regulates SI. In three angiosperm families, including the Solanaceae, the gene that controls the expression of gametophytic SI in the pistil encodes a ribonuclease (S-RNase). The gene that controls pollen SI expression is currently unknown, although several candidates have recently been proposed. Although each candidate shows a high level of polymorphism and complete allelic disequilibrium with the S-RNase gene, such properties may merely reflect tight linkage to the S-locus, irrespective of any functional role in SI. We analyzed the magnitude and nature of nucleotide variation, with the objective of distinguishing likely candidates for regulators of SI from other genes embedded in the S-locus region. We studied the S-RNase gene of the Solanaceae and 48A, a candidate for the pollen gene in this system, and we also conducted a parallel analysis of the regulators of sporophytic SI in Brassica, a system in which both the pistil and pollen genes are known. Although the pattern of variation shown by the pollen gene of the Brassica system is consistent with its role as a determinant of pollen specificity, that of 48A departs from expectation. Our analysis further suggests that recombination between 48A and S-RNase may have occurred during the interval spanned by the gene genealogy, another indication that 48A may not regulate SI expression in pollen.

Construction and validation of a Bovine Innate Immune Microarray

Background: Microarray transcript profiling has the potential to illuminate the molecular processes that are involved in the responses of cattle to disease challenges. This knowledge may allow the development of strategies that exploit these genes to enhance resistance to disease in an individual or animal population. Results: The Bovine Innate Immune Microarray developed in this study consists of 1480 characterised genes identified by literature searches, 31 positive and negative control elements and 5376 cDNAs derived from subtracted and normalised libraries. The cDNA libraries were produced from 'challenged' bovine epithelial and leukocyte cells. The microarray was found to have a limit of detection of 1 pg/mu g of total RNA and a mean slide-to-slide correlation co-efficient of 0.88. The profiles of differentially expressed genes from Concanavalin A ( ConA) stimulated bovine peripheral blood lymphocytes were determined. Three distinct profiles highlighted 19 genes that were rapidly up-regulated within 30 minutes and returned to basal levels by 24 h; 76 genes that were upregulated between 2 - 8 hours and sustained high levels of expression until 24 h and 10 genes that were down-regulated. Quantitative real-time RT-PCR on selected genes was used to confirm the results from the microarray analysis. The results indicate that there is a dynamic process involving gene activation and regulatory mechanisms re-establishing homeostasis in the ConA activated lymphocytes. The Bovine Innate Immune Microarray was also used to determine the cross-species hybridisation capabilities of an ovine PBL sample. Conclusion: The Bovine Innate Immune Microarray has been developed which contains a set of well-characterised genes and anonymous cDNAs from a number of different bovine cell types. The microarray can be used to determine the gene expression profiles underlying innate immune responses in cattle and sheep.

Association between dopamine transporter (DATI) genotype, left-sided inattention, and an enhanced response to methylphenidate in attention-deficit hyperactivity disorder

A polymorphism of the dopamine transporter gene (DAT1, 10-repeat) is associated with attention-deficit hyperactivity disorder (ADHD) and has been linked to an enhanced response to methylphenidate (MPH). One aspect of the attention deficit in ADHD includes a subtle inattention to left space, resembling that seen after right cerebral hemisphere damage. Since left-sided inattention in ADHD may resolve when treated with MPH, we asked whether left-sided inattention in ADHD was related to DAT1 genotype and the therapeutic efficacy of MPH. A total of 43 ADHD children and their parents were genotyped for the DAT1 30 variable number of tandem repeats polymorphism. The children performed the Landmark Test, a well-validated measure yielding a spatial attentional asymmetry index ( leftward to rightward attentional bias). Parents rated their child's response to MPH retrospectively using a three-point scale ( no, mediocre or very good response). Additionally, parents used a symptom checklist to rate behavior while on and off medication. A within-family control design determined whether asymmetry indices predicted biased transmission of 10-repeat parental DAT1 alleles and/or response to MPH. It was found that left-sided inattention predicted transmission of the 10-repeat allele from parents to probands and was associated with the severity of ADHD symptomatology. Children rated as achieving a very good response to MPH displayed left-sided inattention, while those rated as achieving a poorer response did not. Our results suggest a subgroup of children with ADHD for whom the 10-repeat DAT1 allele is associated with left-sided inattention. MPH may be most efficacious in this group because it ameliorates a DAT1-mediated hypodopaminergic state.

Three-dimensional model for multi-component reactive transport with variable density groundwater flow

PHWAT is a new model that couples a geochemical reaction model (PHREEQC-2) with a density-dependent groundwater flow and solute transport model (SEAWAT) using the split-operator approach. PHWAT was developed to simulate multi-component reactive transport in variable density groundwater flow. Fluid density in PHWAT depends not on only the concentration of a single species as in SEAWAT, but also the concentrations of other dissolved chemicals that can be subject to reactive processes. Simulation results of PHWAT and PHREEQC-2 were compared in their predictions of effluent concentration from a column experiment. Both models produced identical results, showing that PHWAT has correctly coupled the sub-packages. PHWAT was then applied to the simulation of a tank experiment in which seawater intrusion was accompanied by cation exchange. The density dependence of the intrusion and the snow-plough effect in the breakthrough curves were reflected in the model simulations, which were in good agreement with the measured breakthrough data. Comparison simulations that, in turn, excluded density effects and reactions allowed us to quantify the marked effect of ignoring these processes. Next, we explored numerical issues involved in the practical application of PHWAT using the example of a dense plume flowing into a tank containing fresh water. It was shown that PHWAT could model physically unstable flow and that numerical instabilities were suppressed. Physical instability developed in the model in accordance with the increase of the modified Rayleigh number for density-dependent flow, in agreement with previous research. (c) 2004 Elsevier Ltd. All rights reserved.

The role of physiological understanding in plant breeding; From a breeding perspective

The role of physiological understanding in improving the efficiency of breeding programs is examined largely from the perspective of conventional breeding programs. Impact of physiological research to date on breeding programs, and the nature of that research, was assessed from (i) responses to a questionnaire distributed to plant breeders and physiologists, and (ii) a survey of literature abstracts. Ways to better utilise physiological understanding for improving breeding programs are suggested, together with possible constraints to delivering beneficial outcomes. Responses from the questionnaire indicated a general view that the contribution by crop physiology to date has been modest. However, most of those surveyed expected the contribution to be larger in the next 20 years. Some constraints to progress perceived by breeders and physiologists were highlighted. The survey of literature abstracts indicated that from a plant breeding perspective, much physiological research is not progressing further than making suggestions about possible approaches to selection. There was limited evidence in the literature of objective comparison of such suggestions with existing methodology, or of development and application of these within active breeding programs. It is argued in this paper that the development of outputs from physiological research for breeding requires a good understanding of the breeding program(s) being serviced and factors affecting its performance. Simple quantitative genetic models, or at least the ideas they represent, should be considered in conducting physiological research and in envisaging and evaluating outputs. The key steps of a generalised breeding program are outlined, and the potential pathways for physiological understanding to impact on these steps are discussed. Impact on breeding programs may arise through (i) better choice of environments in which to conduct selection trials, (ii) identification of selection criteria and traits for focused introgression programs, and (iii) identifying traits for indirect selection criteria as an adjunct to criteria already used. While many breeders and physiologists apparently recognise that physiological understanding may have a major role in the first area, there appears to be relatively Little research activity targeting this issue, and a corresponding bias, arguably unjustified, toward examining traits for indirect selection. Furthermore, research on traits aimed at crop improvement is often deficient because key genetic parameters, such as genetic variation in relevant breeding populations and genetic (as opposed to phenotypic) correlations with yield or other characters of economic importance, are not properly considered in the research. Some areas requiring special attention for successfully interfacing physiology research with breeding are discussed. These include (i) the need to work with relevant genetic populations, (ii) close integration of the physiological research with an active breeding program, and (iii) the dangers of a pre-defined or narrow focus in the physiological research.

Genetic association and cellular function of MC1R variant alleles in human pigmentation

We have examined MC1R variant allele frequencies in the general population of South East Queensland and in a collection of adolescent dizygotic and monozygotic twins and family members to define statistical associations with hair and skin color, freckling, and mole count. Results of these studies are consistent with a linear recessive allelic model with multiplicative penetrance in the inheritance of red hair. Four alleles, D84E, R151C, R160W, and D294H, are strongly associated with red hair and fair skin with multinomial regression analysis showing odds ratios of 63, 118, 50, and 94, respectively. An additional three low-penetrance alleles V60L, V92M, and R163Q have odds ratios 6, 5, and 2 relative to the wild-type allele. To address the cellular effects of MC1R variant alleles in signal transduction, we expressed these receptors in permanently transfected HEK293 cells. Measurement of receptor activity via induction of a cAMP-responsive luciferase reporter gene found that the R151C and R160W receptors were active in the presence of NDP-MSH ligand, but at much reduced levels compared with that seen with the wild-type receptor. The ability to stimulate phosphorylation of the cAMP response element binding protein (CREB) transcription factor was also apparent in all stimulated MC1R variant allele-expressing HEK293 cell extracts as assessed by immunoblotting. In contrast, human melanoma cell lines showed wide variation in the their ability to undergo cAMP-mediated CREB phosphorylation. Culture of human melanocytes of known MC1R genotype may provide the best experimental approach to examine the functional consequences for each MC1R variant allele. With this objective, we have established more than 300 melanocyte cell strains of defined MC1R genotype.